I remember working on a construction site and we did a sloppy job of building forms for a concrete pour. We just slapped some 2x4s and plywood together. I was the new guy and even I could tell it was ugly. I voiced concern and the foreman shrugged. He said, “Close enough for government work.”

I wasn’t working for the government then but I kinda understood it. Disparagement aside, the idea has merit. Especially for the perfectionists and micromanagers. I occasionally fall in both categories.

You may recall the classic dictum: fast, cheap, or good—you can only pick two. When doing something for the first time, many of us make a terrible decision to pick “good and fast.” That is not a place for rookies. Yet we can’t stand the idea of doing something that would be less than the best, something that would merely be “close enough.”

We rookies don’t have the experience to know what that means. But in my example, the foreman absolutely understood. The forms we built for a concrete pour served terrifically for the actual pour and a perfectly good, solid concrete structure was born. Close enough, for the foreman, meant “effective” and “effective” is all you really care about with concrete structures.

Anyway, I sometimes hear people posit an awful thought about Six Sigma—that it should apply to everything. This is well-intentioned ignorance. But first, for those who don’t know, Six Sigma is a brilliant engineering concept that crystallizes the idea of a quality standard that maintains such a level of consistency that outliers are only found on the sixth sigma of a normal statistical distribution.

That leads to an acceptable error rate of 0.00034%. Incredible. Perfectly feasible, too, with today’s manufacturing and engineering practices. Six Sigma is the child of the Total Quality Management. It’s the reason we have cars that last for a million miles. It’s also catnip for perfectionists who wish they were engineers when they’re really just writing a memo.

Two Sigma For The Rest Of Us

“Don’t let perfection get in the way of improvement.” This is a fine adage but I have a love/hate attitude towards the idea. Mostly because it’s an out. I only hear it when someone is tired and wants to quit doing something. Even so, I think there is a way to genuinely embrace this idea and give yourself a consistent way forward.

Ignore Six Sigma, all ye who are laden and doing knowledge work. Do like a construction foreman and adopt Two Sigma instead. Two Sigma, in the realm of standard distribution, ensures that everything stays within your quality standard 95.4% of the time. That’s an error rate of 4.6%. That sounds good enough.

But this assumes you have a quality standard. I hope you do. They’re easy to create. For example, when writing a memo, perhaps it’s as simple as this:

An assurance that the writer has not written in the passive tense 2Pun intended.

Good enough, right? 95 out of 100 memos should adhere to this standard henceforth.

The idea of sigmas, distributions, and error rates establishes statistics as the theme for this week. We started here, with general statistical distribution, as a lead-in to Friday’s review for the book “Naked Statistics: Stripping the Dread From The Data.” It’s a great book on the most powerful, most prevalent mathematics found in the modern world.